14 citations · 16 across the 9 of their papers we have counts for
9 papers
WGDnet: Wishart-guided Geometric-aware Deep Network for PolSAR Image Classification
Junfei Shi, Haojia Zhang, Yu Cheng +1
Polarimetric Synthetic Aperture Radar (PolSAR) classification underpins all-weather Earth observation. Conventional Wishart methods depend on rigid handcrafted operators with limit…
Direction-adaptive Mamba: Spatial-Frequency Dual-Domain Collaborative Learning for PolSAR Image Classification
Junfei Shi, Yu Cheng, Haojia Zhang +3
Deep learning dominates polarimetric synthetic aperture radar (PolSAR) image classification, with Mamba architectures serving as favorable backbones due to linear complexity and st…
Multiview Manifold Evidential Fusion for PolSAR Image Classification
Junfei Shi, Haojia Zhang, Haiyan Jin +5
Polarimetric Synthetic Aperture Radar (PolSAR) covariance matrices and their extracted multi-features - such as scattering angle, entropy, texture, and boundary descriptors - provi…
Knowledge-guided Complex Diffusion Model for PolSAR Image Classification in Contourlet Domain
Junfei Shi, Yu Cheng, Haiyan Jin +4
Diffusion models have demonstrated exceptional performance across various domains due to their ability to model and generate complicated data distributions. However, when applied t…
A Novel Riemannian Sparse Representation Learning Network for Polarimetric SAR Image Classification
Junfei Shi, Mengmeng Nie, Weisi Lin +3
Deep learning is an effective end-to-end method for Polarimetric Synthetic Aperture Radar(PolSAR) image classification, but it lacks the guidance of related mathematical principle…
Riemannian Complex Hermit Positive Definite Convolution Network for Polarimetric SAR Image Classification
Junfei Shi, Yuke Li, Mengmeng Nie +4
Deep learning has been extensively utilized for PolSAR image classification. However, most existing methods transform the polarimetric covariance matrix into a real- or complex-val…
Riemannian Complex Matrix Convolution Network for PolSAR Image Classification
Junfei Shi, Wei Wang, Haiyan Jin +2
Recently, deep learning methods have achieved superior performance for Polarimetric Synthetic Aperture Radar(PolSAR) image classification. Existing deep learning methods learn PolS…
Riemannian Nearest-Regularized Subspace Classification for Polarimetric SAR images
Junfei Shi, Haiyan Jin
As a representation learning method, nearest regularized subspace(NRS) algorithm is an effective tool to obtain both accuracy and speed for PolSAR image classification. However, ex…
Polarimetric Hierarchical Semantic Model and Scattering Mechanism Based PolSAR Image Classification
Fang Liu, Junfei Shi, Licheng Jiao +5
For polarimetric SAR (PolSAR) image classification, it is a challenge to classify the aggregated terrain types, such as the urban area, into semantic homogenous regions due to shar…